64,653 research outputs found
Transient dynamics of a one-dimensional Holstein polaron under the influence of an external electric field
Following the Dirac-Frenkel time-dependent variational principle, transient
dynamics of a one-dimensional Holstein polaron with diagonal and off-diagonal
exciton-phonon coupling in an external electric field is studied by employing
the multi-D {\it Ansatz}, also known as a superposition of the usual
Davydov D trial states. Resultant polaron dynamics has significantly
enhanced accuracy, and is in perfect agreement with that derived from the
hierarchy equations of motion method. Starting from an initial broad wave
packet, the exciton undergoes typical Bloch oscillations. Adding weak
exciton-phonon coupling leads to a broadened exciton wave packet and a reduced
current amplitude. Using a narrow wave packet as the initial state, the bare
exciton oscillates in a symmetric breathing mode, but the symmetry is easily
broken by weak coupling to phonons, resulting in a non-zero exciton current.
For both scenarios, temporal periodicity is unchanged by exciton-phonon
coupling. In particular, at variance with the case of an infinite linear chain,
no steady state is found in a finite-sized ring within the anti-adiabatic
regime. For strong diagonal coupling, the multi- {\it Anstaz} is found
to be highly accurate, and the phonon confinement gives rise to exciton
localization and decay of the Bloch oscillations
Fast, Accurate Thin-Structure Obstacle Detection for Autonomous Mobile Robots
Safety is paramount for mobile robotic platforms such as self-driving cars
and unmanned aerial vehicles. This work is devoted to a task that is
indispensable for safety yet was largely overlooked in the past -- detecting
obstacles that are of very thin structures, such as wires, cables and tree
branches. This is a challenging problem, as thin objects can be problematic for
active sensors such as lidar and sonar and even for stereo cameras. In this
work, we propose to use video sequences for thin obstacle detection. We
represent obstacles with edges in the video frames, and reconstruct them in 3D
using efficient edge-based visual odometry techniques. We provide both a
monocular camera solution and a stereo camera solution. The former incorporates
Inertial Measurement Unit (IMU) data to solve scale ambiguity, while the latter
enjoys a novel, purely vision-based solution. Experiments demonstrated that the
proposed methods are fast and able to detect thin obstacles robustly and
accurately under various conditions.Comment: Appeared at IEEE CVPR 2017 Workshop on Embedded Visio
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